NK細胞受容体の安静時空間統計が早期シグナル識別を改善する可能性がある

Natural Killer (NK) cells are lymphocytes of the innate immunity and sense healthy or diseased target cells with activating and inhibitory NK cell receptor (NKR) molecules expressed on the cell surface. The protection provided by NK cells against viral infections and tumors critically depends on their ability to distinguish healthy cells from diseased target cells that express 100-fold more activating ligands. NK cell signaling and activation depend on integrating opposing signals initiated by activating and inhibitory NKRs interacting with the cognate ligands expressed on target cells. Imaging experiments show that both activating and inhibitory NKRs in the plasma membrane form submicron-sized clusters in resting NK cells. How do these submicron size NKR clusters formed in the resting state affect signal discrimination? Using in silico mechanistic signaling modeling combined with information theory and published super-resolution imaging data for two well-studied human NKRs, activating NKG2D and inhibitory KIR2DL1, we show that early time signal discrimination by NK cells depends on the spatial statistics of these clusters. Modeling shows when NKG2D and KIR2DL1 clusters are disjoint in the resting state, these clusters help NK cells to discriminate between target cells expressing low and high levels of the activating cognate ligand, whereas, when the NKR clusters show high degree of overlap it prevents NK cells from differentiating healthy from diseased target cells. Therefore, the spatial statistics of submicron scale clusters of activating and inhibitory NKRs at the resting state provides an additional layer of control for signal discrimination in NK cells.